gpt-academic3.6 / crazy_functions /总结音视频.py
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from toolbox import CatchException, report_execption, select_api_key, update_ui, write_results_to_file
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
def split_audio_file(filename, split_duration=1000):
"""
根据给定的切割时长将音频文件切割成多个片段。
Args:
filename (str): 需要被切割的音频文件名。
split_duration (int, optional): 每个切割音频片段的时长(以秒为单位)。默认值为1000。
Returns:
filelist (list): 一个包含所有切割音频片段文件路径的列表。
"""
from moviepy.editor import AudioFileClip
import os
os.makedirs('gpt_log/mp3/cut/', exist_ok=True) # 创建存储切割音频的文件夹
# 读取音频文件
audio = AudioFileClip(filename)
# 计算文件总时长和切割点
total_duration = audio.duration
split_points = list(range(0, int(total_duration), split_duration))
split_points.append(int(total_duration))
filelist = []
# 切割音频文件
for i in range(len(split_points) - 1):
start_time = split_points[i]
end_time = split_points[i + 1]
split_audio = audio.subclip(start_time, end_time)
split_audio.write_audiofile(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
filelist.append(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
audio.close()
return filelist
def AnalyAudio(file_manifest, llm_kwargs, chatbot, history):
import os, requests
from moviepy.editor import AudioFileClip
from request_llm.bridge_all import model_info
# 设置OpenAI密钥和模型
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
whisper_endpoint = chat_endpoint.replace('chat/completions', 'audio/transcriptions')
url = whisper_endpoint
headers = {
'Authorization': f"Bearer {api_key}"
}
os.makedirs('gpt_log/mp3/', exist_ok=True)
for index, fp in enumerate(file_manifest):
audio_history = []
# 提取文件扩展名
ext = os.path.splitext(fp)[1]
# 提取视频中的音频
if ext not in [".mp3", ".wav", ".m4a", ".mpga"]:
audio_clip = AudioFileClip(fp)
audio_clip.write_audiofile(f'gpt_log/mp3/output{index}.mp3')
fp = f'gpt_log/mp3/output{index}.mp3'
# 调用whisper模型音频转文字
voice = split_audio_file(fp)
for j, i in enumerate(voice):
with open(i, 'rb') as f:
file_content = f.read() # 读取文件内容到内存
files = {
'file': (os.path.basename(i), file_content),
}
data = {
"model": "whisper-1",
'response_format': "text"
}
response = requests.post(url, headers=headers, files=files, data=data).text
i_say = f'请对下面的文章片段做概述,文章内容是 ```{response}```'
i_say_show_user = f'第{index + 1}段音频的第{j + 1} / {len(voice)}片段。'
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say,
inputs_show_user=i_say_show_user,
llm_kwargs=llm_kwargs,
chatbot=chatbot,
history=[],
sys_prompt="总结文章。"
)
chatbot[-1] = (i_say_show_user, gpt_say)
history.extend([i_say_show_user, gpt_say])
audio_history.extend([i_say_show_user, gpt_say])
# 已经对该文章的所有片段总结完毕,如果文章被切分了,
result = "".join(audio_history)
if len(audio_history) > 1:
i_say = f"根据以上的对话,使用中文总结文章{result}的主要内容。"
i_say_show_user = f'第{index + 1}段音频的主要内容:'
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say,
inputs_show_user=i_say_show_user,
llm_kwargs=llm_kwargs,
chatbot=chatbot,
history=audio_history,
sys_prompt="总结文章。"
)
history.extend([i_say, gpt_say])
audio_history.extend([i_say, gpt_say])
res = write_results_to_file(history)
chatbot.append((f"第{index + 1}段音频完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 删除中间文件夹
import shutil
shutil.rmtree('gpt_log/mp3')
res = write_results_to_file(history)
chatbot.append(("所有音频都总结完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history)
@CatchException
def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, WEB_PORT):
import glob, os
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"总结音视频内容,函数插件贡献者: dalvqw"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
try:
from moviepy.editor import AudioFileClip
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade moviepy```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 清空历史,以免输入溢出
history = []
# 检测输入参数,如没有给定输入参数,直接退出
if os.path.exists(txt):
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 搜索需要处理的文件清单
extensions = ['.mp4', '.m4a', '.wav', '.mpga', '.mpeg', '.mp3', '.avi', '.mkv', '.flac', '.aac']
if txt.endswith(tuple(extensions)):
file_manifest = [txt]
else:
file_manifest = []
for extension in extensions:
file_manifest.extend(glob.glob(f'{project_folder}/**/*{extension}', recursive=True))
# 如果没找到任何文件
if len(file_manifest) == 0:
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何音频或视频文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 开始正式执行任务
yield from AnalyAudio(file_manifest, llm_kwargs, chatbot, history)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面